Seismic Wavefield Sampling

Vermeer, Gijs J. O.

doi:10.1190/1.9781560802440

Cited by 57 publications

(42 citation statements)

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“…Even when the signal (primary energy) is properly sampled, organized noise, such as ground roll and multiples, is often undersampled, especially in areas where the noise has a much lower velocity than the signal. Although normal moveout (NMO) correction is sometimes used to reduce aliasing for some recording geometries (such as offend marine shooting), an inherent aliasing problem remains in the common offset and common midpoint (CMP) domains, even when source and receiver domains are properly sampled (Vermeer, 1990). Shot intervals that are larger than receiver intervals compound the aliasing problem.…”

Section: Introductionmentioning

confidence: 98%

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Seismic trace interpolation in the Fourier transform domain

Gülünay¹

2003

GEOPHYSICS

195

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A data adaptive interpolation method is designed and applied in the Fourier transform domain (f‐k or f‐kx‐ky for spatially aliased data. The method makes use of fast Fourier transforms and their cyclic properties, thereby offering a significant cost advantage over other techniques that interpolate aliased data. The algorithm designs and applies interpolation operators in the f‐k (or f‐kx‐ky domain to fill zero traces inserted in the data in the t‐x (or t‐x‐y) domain at locations where interpolated traces are needed. The interpolation operator is designed by manipulating the lower frequency components of the stretched transforms of the original data. This operator is derived assuming that it is the same operator that fills periodically zeroed traces of the original data but at the lower frequencies, and corresponds to the f‐k (or f‐kx‐ky domain version of the well‐known f‐x (or f‐x‐y) domain trace interpolators. The method is applicable to 2D and 3D data recorded sparsely in a horizontal plane. The most common prestack applications of the algorithm are common‐mid‐point domain shot interpolation, source‐receiver domain shot interpolation, and cable interpolation.

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Section: Introductionmentioning

confidence: 98%

“…Ideally, source and receiver intervals should be chosen so that reconstruction of the continuous wavefield from the recorded samples is possible. The data are then said to be "properly sampled" (Vermeer, 1990). The resulting source and receiver intervals are called "basic sampling intervals.…”

Section: Introductionmentioning

confidence: 99%

Seismic trace interpolation in the Fourier transform domain

Gülünay¹

2003

GEOPHYSICS

195

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“…Irregular sampling leads, for example, to a leaking stack operator (see Vermeer, 1990), and to problems with f -k filtering (which is based on the Fourier transform and, consequently, requires that the data are regularly sampled). In the case of irregular sampling, signal may not be preserved completely and noise may not be optimally attenuated.…”

Section: Introductionmentioning

confidence: 99%

A general reconstruction scheme for dominant azimuth 3D seismic data

Schonewille¹,

Romijn²,

Duijndam

et al. 2003

GEOPHYSICS

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Seismic data are usually irregularly and sparsely sampled along the spatial coordinates, which yields suboptimal imaging results. For time-lapse data, differences in the spatial sampling of base and monitor surveys lead to undesired differences between the images of the surveys that are not due to differences in the subsurface.In this paper, an efficient two-step reconstruction method is proposed for irregularly and sparsely sampled 3D seismic data recorded with a dominant azimuth for large offsets. The first step is reconstruction along the receiver lines such that the midpoints are exactly on crosslines. The second step is a 2D reconstruction in the crossline midpoint-offset domain using a least-squares estimation of Fourier components.Sparse sampling can be handled by optimizing the parameterization of the least-squares estimation of the Fourier coefficients, and consequently it is possible to reconstruct data that would be aliased when considering single common-midpoint gathers.The method can be used to do a geometry transformation of the data to any desired spatial grid. Since the method yields consistent results independent of the actual sampling, it is very well suited for 4D processing.

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“…1b) and spatial sampling intervals of 5 m for the case of for a=50 m (Fig. 1c The frequency-wavenumber (f-k) diagram is helpful for visualizing the sampling of a continuous wave field (Vermeer, 1990). The time window (from 0.65 to 1.05 s) including only scattered wave fields was extracted from each shot gather to calculate an f-k plot.…”

Section: Wave Field Calculationmentioning

confidence: 99%

“…Thus, quarter-wavelength spatial sampling is a minimum requirement for adequate recording. Vermeer (1990) defined the term " full-resolution recording" for unaliased shooting and recording of the seismic wave field at the basic signal-sampling interval. In practice, however, seismic data are often irregularly and/ or sparsely sampled in the space domain because of limitations such as those resulting from difficult topography or a lack of resources.…”

Section: Spatial Sampling Interval In Seismic Reflectionmentioning

confidence: 99%

Effects of Random Heterogeneity on Seismic Reflection Images

Matsushima¹

2012

Seismic Waves - Research and Analysis

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Seismic Wavefield Sampling

Cited by 57 publications

References 0 publications

Seismic trace interpolation in the Fourier transform domain

Seismic trace interpolation in the Fourier transform domain

A general reconstruction scheme for dominant azimuth 3D seismic data

Effects of Random Heterogeneity on Seismic Reflection Images

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